Publication Details

Task Inference and Distributed Task Management in the Centibots Robotic System

by Ortiz, C. and Vincent, R. and Morisset, B.

in The Fourth International Joint Conference on Autonomous Agents and Multi Agent Systems

Published by ACMJul 2005.

Abstract

We describe the Centibots system, a very large scale distributed
robotic system, consisting of more than 100 robots, that has been
successfully deployed in large, unknown indoor environments, over
extended periods of time (i.e., durations corresponding to several
power cycles). Unlike most multiagent systems, the set of tasks about
which teams must collaborate is not given {\it a priori}. We first
describe a task inference algorithm that identifies potential team
commitments that collectively balance constraints such as
reachability, sensor coverage, and communication access. We then
describe a dispatch algorithm for task distribution and management
that assigns resources depending on either task density or
replacement requirements stemming from failures or power shortages.
The targeted deployment environments are expected to lack a supporting
communication infrastructure; robots manage their own network and
reason about the concomitant localization constraints necessary to
maintain team communication. Finally, we present quantitative
results in terms of a ``search and rescue problem and discuss the
team-oriented aspects of the system in the context of prevailing
theories of multiagent collaboration.

Electronic Copies

Associated Projects

This is a joint project with Stanford, University of Washington, and ActiveMedia Robotics, to design, implement and demonstrate a computational framework for the coordination of very large robot teams, consisting of at least 100 small, resource limited robots, on an indoor reconnaissance task.